Pursuer Navigation Based on Proportional Navigation and Optimal Information Fusion

Pursuer navigation is proposed based on the three-dimensional proportional navigation law, and this method presents a family of navigation laws resulting in a rich behavior for different parameters. Firstly, the kinematics model for the pursuer and the target is established. Secondly, the proportional navigation law is deduced through the kinematics model. Based on point-to-point navigation, obstacle avoidance is implemented by adjusting the control parameters, and the combination can enrich the application range of obstacle avoidance and guidance laws. Thirdly, information fusion weighted by diagonal matrices is used for decreasing the tracking precision. Finally, simulations are conducted in the MATLAB environment. Simulation results verify the availability of the proposed navigation law.

Intercepting Higher-Speed Targets Using Generalized Relative Biased Proportional Navigation

To intercept a higher-speed target in the terminal guidance phase, this paper proposes a generalized relative biased proportional navigation (BPN) law. In order to enlarge the capture domain of the classical proportional navigation (PN) law and make full use of the maneuverability of a missile, the paper designs time-varying navigation coefficients; thus the modified PN guidance law integrates the advantages of the PN guidance law with those of the retro-PN guidance law. In order to intercept high-speed targets with impact angle constraints, the relative BPN law is introduced, and the impact angle is achieved by controlling the relative flight-path angle. In order to improve the performance of the guidance law for intercepting higher-speed maneuvering targets, some compensation measures are designed for guidance commands. Extensive simulations are conducted to verify the design features of the proportional navigation law.

Proportional Navigation and Model Predictive Control of an Unmanned Autonomous Vehicle for Obstacle Avoidance

This paper presents a new approach for the guidance and control of a UGV (Unmanned Ground Vehicle). An obstacle avoidance algorithm was developed using an integrated system involving proportional navigation (PN) and a nonlinear model predictive controller (NMPC). An obstacle avoidance variant of the classical proportional navigation law generates command lateral accelerations to avoid obstacles, while the NMPC is used to track the reference trajectory given by the PN. The NMPC utilizes a lateral vehicle dynamic model. Obstacle avoidance has become a popular area of research for both unmanned aerial vehicles and unmanned ground vehicles. In this application an obstacle avoidance algorithm can take over the control of a vehicle until the obstacle is no longer a threat. The performance of the obstacle avoidance algorithm is evaluated through simulation. Simulation results show a promising approach to conditionally implemented obstacle avoidance.

A 3D pitch and impact-angle constrained guidance scheme

In this paper, a guidance scheme for achieving all the possible impact angles constraints for 3D engagements is proposed. For a simple and computationally efficient solution, our approach considers proportional navigation based impact-angle constrained guidance. However, the 3D proportional navigation law cannot be directly applied. This paper proposes a guidance strategy in which a 3D problem is divided into two consecutive 2D problems using a temporary target. The missile switches between the two planes using a temporary target. The paper begins with a simple approach and finally proposes a realistic solution. In all the scenarios considered, the guidance scheme achieves the desired impact angles. To further increase its effectiveness, the paper considers pitch constrained impact-angle law that drives the terminal angle of attack to zero. This ensures that the body axis of the missile will be aligned with its velocity vector at the time of impact. The effectiveness of the proposed guidance schemes are systematically verified through numerical simulations considering both kinematic and realistic models with first-order autopilot lag.